Ignore:
Timestamp:
03/15/12 15:14:54 (2 years ago)
Author:
anzeh <anze.staric@…>
Branch:
default
Message:

Moved preprocess from Orange to Orange.data.

File:
1 moved

Legend:

Unmodified
Added
Removed
  • docs/reference/rst/Orange.data.preprocess.rst

    r10053 r10542  
    33############################## 
    44 
    5 .. automodule:: Orange.preprocess 
     5.. automodule:: Orange.data.preprocess 
    66 
    7 .. automodule:: Orange.preprocess.scaling 
     7.. autoclass:: DiscretizeEntropy(method=Orange.feature.discretization.Entropy()) 
     8 
     9.. autoclass:: RemoveContinuous 
     10 
     11.. autoclass:: Continuize 
     12 
     13.. autoclass:: RemoveDiscrete 
     14 
     15.. autoclass:: Impute 
     16 
     17.. autoclass:: FeatureSelection(measure=Orange.feature.scoring.Relief(), filter=None, limit=10) 
     18 
     19.. autofunction:: bestP 
     20 
     21.. autofunction:: bestN 
     22 
     23.. autofunction:: selectNRandom 
     24 
     25.. autofunction:: selectPRandom 
     26 
     27.. autoclass:: RFE 
     28 
     29.. autoclass:: Sample 
     30 
     31.. autoclass:: PreprocessorList 
     32 
     33.. class:: RemoveUnusedValues(variable, data, remove_one_valued=False) 
     34 
     35    Removes unused values and reduces the variable, if a variable 
     36    declares values that do not appear in the data. 
     37 
     38    :param variable: :obj:`~Orange.feature.Descriptor` 
     39    :param data: :obj:`~Orange.data.Table` 
     40    :param remove_one_valued: Decides whether to remove or to retain 
     41        the attributes with only one value defined (default: False). 
     42 
     43    Example: 
     44 
     45    .. literalinclude:: code/unusedValues.py 
     46 
     47    There are four possible outcomes: 
     48 
     49    1. The variable does not have any used values in the data - value 
     50    of this variable is undefined for all examples. The variable is 
     51    thus useless and the class returns None. 
     52 
     53    2. The variable has only one used value (or, possibly, only one 
     54    value at all). Such a variable is in fact useless, and can 
     55    probably be removed without harm. Nevertheless, its fate is 
     56    decided by the flag remove_one_valued which is False by default, 
     57    so such variables are retained unless explicitly specified 
     58    otherwise. 
     59 
     60    3. All variable's values occur in the data (and the variable has more 
     61    than one value; otherwise the above case applies). The original variable 
     62    is returned. 
     63 
     64    4. There are some unused values. A new variable is constructed and the 
     65    unused values are omitted. The value of the new variable is computed 
     66    automatically from the value of the original variable 
     67    :class:`~Orange.classification.lookup.ClassifierByLookupTable` is used 
     68    for mapping. 
     69 
     70    Results of example: 
     71 
     72    .. literalinclude:: code/unusedValues.res 
     73 
     74    Variables a and y are OK and are left alone. In b, value 1 is not used 
     75    and is removed (not in the original variable, of course; a new variable 
     76    is created). c is useless and is removed altogether. d is retained since 
     77    remove_one_valued was left at False; if we set it to True, this variable 
     78    would be removed as well. 
     79 
     80 
     81.. automodule:: Orange.data.preprocess.scaling 
Note: See TracChangeset for help on using the changeset viewer.